In this experiment I am observing a co-evolving population (survival is determined by a random draw) with a non-interactible trait. I expect to see no spatial phenotype correlation
What happens when a co-evolving trait is not interitable?
## All cor, lit, and grid files exist!
## This program will now end!
file_name= “Snake_1e-11_5_Newt_1e-11_5_0” file_name= “Snake_1e-08_0.005_Newt_1e-08_0.005_3” inter_tall_tall_file inter_cor_tall_file inter_inter_grid_tall_file
notes
notes
## Group.1 x
## 1 1e-08_0.005_1e-08_0.005 -0.18729482
## 2 1e-08_0.005_1e-09_0.05 0.13976018
## 3 1e-08_0.005_1e-10_0.5 0.50759825
## 4 1e-08_0.005_1e-11_5 1.07418888
## 5 1e-09_0.05_1e-08_0.005 -0.11800217
## 6 1e-09_0.05_1e-09_0.05 -0.08351749
## 7 1e-09_0.05_1e-10_0.5 0.57878556
## 8 1e-09_0.05_1e-11_5 0.74688826
## 9 1e-10_0.5_1e-08_0.005 -0.61776623
## 10 1e-10_0.5_1e-09_0.05 -0.59585200
## 11 1e-10_0.5_1e-10_0.5 0.02503837
## 12 1e-10_0.5_1e-11_5 0.45853498
## 13 1e-11_5_1e-08_0.005 -0.97525745
## 14 1e-11_5_1e-09_0.05 -0.47443100
## 15 1e-11_5_1e-10_0.5 -0.42495875
## 16 1e-11_5_1e-11_5 0.04003739
Explain
Notes
explain
notes
After looking at this figure, I can see that there is a larger range of correlation values. The can sometimes be positive, near 0, or negative. Very few reach (or come near) the real newt-snake correlation. How do you find the correct time slice to look for spatial correlation? How would these phenotypes become spatially correlated and then become not spatially correlated.
In order to understand how spatial correlations where changing with time I took 5,000 generation time slices to look at all four trials correlation values. Each color is a different trial per GA combination. The histogram values are stacked.
exp
notes
## [1] "pattern 1e-08_0.005_1e-09_0.05_1"
## [1] "Cor between average snake pheno and local cor -0.177345827911184"
## [1] "Cor between average newt pheno and local cor -0.177394682818902"
## [1] "Cor between average dif pheno and local cor 0.118831497227703"
## [1] "Cor between newt pheno and snake -0.270520115883644"
## [1] "pattern 1e-09_0.05_1e-11_5_0"
## [1] "Cor between average snake pheno and local cor 0.16777243970841"
## [1] "Cor between average newt pheno and local cor -0.00726983202923471"
## [1] "Cor between average dif pheno and local cor 0.133559933250909"
## [1] "Cor between newt pheno and snake 0.600181538612102"
I still wonder why the correlation values go up and down, because the mean newt and snake phenotype keeps going up. I wonder if the individuals might be moving around too much. I wonder what would happen on a larger map?
This next section is just getting a glimpse at how newt & snake phenotype and population size differ over time. The populations start off with about 250 individuals each. Each individual has a different genetic background created from msprime.
explane
notes
expla
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exp
notes
## [1] 0.08941538
## [1] -0.05684025
## [1] -0.05620503
## [1] -0.1811683
## [1] -0.2839627
## [1] -0.2447956
## [1] 0.2091648
## [1] -0.19622
## [1] 0.01225089
## [1] 0.6059479
## [1] 0.07210036
## [1] 0.4470126
## [1] 0.241293
## [1] 0.08881336
## [1] 0.440485